{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lab 7 & 8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Where for dataset\n",
    "\n",
    "[UCI Official - Classification](https://archive.ics.uci.edu/ml/datasets.php?format=&task=cla&att=&area=&numAtt=&numIns=&type=&sort=taskUp&view=table)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset for this lab\n",
    "\n",
    "[UCI - Room Occupancy Estimation Data Set](https://archive.ics.uci.edu/ml/datasets/Room+Occupancy+Estimation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import modules\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from sklearn import svm, tree, model_selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>S1_Temp</th>\n",
       "      <th>S2_Temp</th>\n",
       "      <th>S3_Temp</th>\n",
       "      <th>S4_Temp</th>\n",
       "      <th>S1_Light</th>\n",
       "      <th>S2_Light</th>\n",
       "      <th>S3_Light</th>\n",
       "      <th>S4_Light</th>\n",
       "      <th>S1_Sound</th>\n",
       "      <th>S2_Sound</th>\n",
       "      <th>S3_Sound</th>\n",
       "      <th>S4_Sound</th>\n",
       "      <th>S5_CO2</th>\n",
       "      <th>S5_CO2_Slope</th>\n",
       "      <th>S6_PIR</th>\n",
       "      <th>S7_PIR</th>\n",
       "      <th>Room_Occupancy_Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017/12/22</td>\n",
       "      <td>10:49:41</td>\n",
       "      <td>24.94</td>\n",
       "      <td>24.75</td>\n",
       "      <td>24.56</td>\n",
       "      <td>25.38</td>\n",
       "      <td>121</td>\n",
       "      <td>34</td>\n",
       "      <td>53</td>\n",
       "      <td>40</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.06</td>\n",
       "      <td>390</td>\n",
       "      <td>0.769231</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017/12/22</td>\n",
       "      <td>11:03:28</td>\n",
       "      <td>25.13</td>\n",
       "      <td>24.88</td>\n",
       "      <td>24.69</td>\n",
       "      <td>25.56</td>\n",
       "      <td>123</td>\n",
       "      <td>35</td>\n",
       "      <td>58</td>\n",
       "      <td>44</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.09</td>\n",
       "      <td>410</td>\n",
       "      <td>0.607692</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017/12/22</td>\n",
       "      <td>11:17:15</td>\n",
       "      <td>25.25</td>\n",
       "      <td>24.94</td>\n",
       "      <td>24.75</td>\n",
       "      <td>25.69</td>\n",
       "      <td>123</td>\n",
       "      <td>35</td>\n",
       "      <td>60</td>\n",
       "      <td>45</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.08</td>\n",
       "      <td>430</td>\n",
       "      <td>0.946154</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017/12/22</td>\n",
       "      <td>11:31:33</td>\n",
       "      <td>25.38</td>\n",
       "      <td>25.44</td>\n",
       "      <td>24.81</td>\n",
       "      <td>25.81</td>\n",
       "      <td>157</td>\n",
       "      <td>242</td>\n",
       "      <td>69</td>\n",
       "      <td>54</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.16</td>\n",
       "      <td>450</td>\n",
       "      <td>0.538462</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017/12/22</td>\n",
       "      <td>11:47:23</td>\n",
       "      <td>25.50</td>\n",
       "      <td>25.63</td>\n",
       "      <td>24.94</td>\n",
       "      <td>25.81</td>\n",
       "      <td>155</td>\n",
       "      <td>234</td>\n",
       "      <td>73</td>\n",
       "      <td>56</td>\n",
       "      <td>1.02</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.13</td>\n",
       "      <td>530</td>\n",
       "      <td>3.738462</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>2018/01/11</td>\n",
       "      <td>08:02:28</td>\n",
       "      <td>25.06</td>\n",
       "      <td>25.06</td>\n",
       "      <td>24.56</td>\n",
       "      <td>25.13</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>16</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.09</td>\n",
       "      <td>345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>2018/01/11</td>\n",
       "      <td>08:16:45</td>\n",
       "      <td>25.13</td>\n",
       "      <td>25.06</td>\n",
       "      <td>24.63</td>\n",
       "      <td>25.13</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>29</td>\n",
       "      <td>20</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.08</td>\n",
       "      <td>345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>2018/01/11</td>\n",
       "      <td>08:30:33</td>\n",
       "      <td>25.13</td>\n",
       "      <td>25.06</td>\n",
       "      <td>24.63</td>\n",
       "      <td>25.13</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>31</td>\n",
       "      <td>21</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.09</td>\n",
       "      <td>345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>2018/01/11</td>\n",
       "      <td>08:44:20</td>\n",
       "      <td>25.13</td>\n",
       "      <td>25.06</td>\n",
       "      <td>24.63</td>\n",
       "      <td>25.19</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>32</td>\n",
       "      <td>21</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.08</td>\n",
       "      <td>345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>2018/01/11</td>\n",
       "      <td>08:58:37</td>\n",
       "      <td>25.06</td>\n",
       "      <td>25.06</td>\n",
       "      <td>24.69</td>\n",
       "      <td>25.25</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>34</td>\n",
       "      <td>22</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.08</td>\n",
       "      <td>345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>376 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date      Time  S1_Temp  S2_Temp  S3_Temp  S4_Temp  S1_Light  \\\n",
       "0    2017/12/22  10:49:41    24.94    24.75    24.56    25.38       121   \n",
       "1    2017/12/22  11:03:28    25.13    24.88    24.69    25.56       123   \n",
       "2    2017/12/22  11:17:15    25.25    24.94    24.75    25.69       123   \n",
       "3    2017/12/22  11:31:33    25.38    25.44    24.81    25.81       157   \n",
       "4    2017/12/22  11:47:23    25.50    25.63    24.94    25.81       155   \n",
       "..          ...       ...      ...      ...      ...      ...       ...   \n",
       "371  2018/01/11  08:02:28    25.06    25.06    24.56    25.13         5   \n",
       "372  2018/01/11  08:16:45    25.13    25.06    24.63    25.13         5   \n",
       "373  2018/01/11  08:30:33    25.13    25.06    24.63    25.13         6   \n",
       "374  2018/01/11  08:44:20    25.13    25.06    24.63    25.19         6   \n",
       "375  2018/01/11  08:58:37    25.06    25.06    24.69    25.25         6   \n",
       "\n",
       "     S2_Light  S3_Light  S4_Light  S1_Sound  S2_Sound  S3_Sound  S4_Sound  \\\n",
       "0          34        53        40      0.08      0.19      0.06      0.06   \n",
       "1          35        58        44      0.44      0.13      0.17      0.09   \n",
       "2          35        60        45      0.93      0.14      0.12      0.08   \n",
       "3         242        69        54      0.58      0.56      0.25      0.16   \n",
       "4         234        73        56      1.02      0.29      0.16      0.13   \n",
       "..        ...       ...       ...       ...       ...       ...       ...   \n",
       "371         5        23        16      0.07      0.04      0.05      0.09   \n",
       "372         6        29        20      0.08      0.05      0.06      0.08   \n",
       "373         6        31        21      0.08      0.05      0.05      0.09   \n",
       "374         7        32        21      0.08      0.05      0.05      0.08   \n",
       "375         7        34        22      0.07      0.05      0.05      0.08   \n",
       "\n",
       "     S5_CO2  S5_CO2_Slope  S6_PIR  S7_PIR  Room_Occupancy_Count  \n",
       "0       390      0.769231       0       0                     1  \n",
       "1       410      0.607692       1       0                     1  \n",
       "2       430      0.946154       1       0                     1  \n",
       "3       450      0.538462       0       1                     2  \n",
       "4       530      3.738462       1       1                     2  \n",
       "..      ...           ...     ...     ...                   ...  \n",
       "371     345      0.000000       0       0                     0  \n",
       "372     345      0.000000       0       0                     0  \n",
       "373     345      0.000000       0       0                     0  \n",
       "374     345      0.000000       0       0                     0  \n",
       "375     345      0.000000       0       0                     0  \n",
       "\n",
       "[376 rows x 19 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read dataset\n",
    "dataset = pd.read_csv('Occupancy/Occupancy_Estimation.csv') # Read dataset\n",
    "dataset = pd.DataFrame(dataset[::27]).reset_index().drop('index', axis=1)\n",
    "dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[24.94 24.75]\n",
      " [25.13 24.88]\n",
      " [25.25 24.94]\n",
      " [25.38 25.44]\n",
      " [25.5  25.63]\n",
      " [25.56 27.25]\n",
      " [25.69 28.19]\n",
      " [25.69 28.38]\n",
      " [25.94 28.19]\n",
      " [25.94 27.75]\n",
      " [26.06 27.38]\n",
      " [26.06 27.  ]\n",
      " [26.19 27.13]\n",
      " [26.13 26.81]\n",
      " [26.06 26.38]\n",
      " [26.   26.19]\n",
      " [25.94 26.06]\n",
      " [25.81 25.88]\n",
      " [25.88 25.88]\n",
      " [26.   25.81]\n",
      " [26.   25.81]\n",
      " [26.06 25.75]\n",
      " [26.13 25.69]\n",
      " [26.13 25.75]\n",
      " [26.13 25.75]\n",
      " [26.19 25.75]\n",
      " [26.19 25.75]\n",
      " [26.25 25.94]\n",
      " [26.25 25.94]\n",
      " [26.31 26.38]\n",
      " [26.31 26.38]\n",
      " [26.25 26.63]\n",
      " [26.31 26.63]\n",
      " [26.31 27.88]\n",
      " [26.38 27.88]\n",
      " [26.31 28.13]\n",
      " [26.25 26.69]\n",
      " [26.06 26.31]\n",
      " [25.94 26.13]\n",
      " [25.88 26.  ]\n",
      " [25.81 25.94]\n",
      " [25.81 25.88]\n",
      " [25.75 25.75]\n",
      " [25.69 25.75]\n",
      " [25.63 25.69]\n",
      " [25.63 25.63]\n",
      " [25.63 25.63]\n",
      " [25.56 25.56]\n",
      " [25.56 25.56]\n",
      " [25.5  25.5 ]\n",
      " [25.5  25.5 ]\n",
      " [25.44 25.5 ]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.25 25.25]\n",
      " [25.25 25.25]\n",
      " [25.19 25.25]\n",
      " [25.25 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.13 25.19]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.06 25.13]\n",
      " [25.06 25.13]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.  ]\n",
      " [25.06 25.06]\n",
      " [25.   25.06]\n",
      " [25.06 25.  ]\n",
      " [25.   25.06]\n",
      " [25.06 25.  ]\n",
      " [25.06 25.06]\n",
      " [25.   25.06]\n",
      " [25.   25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.31 25.31]\n",
      " [25.44 25.25]\n",
      " [25.56 25.31]\n",
      " [25.69 25.38]\n",
      " [25.69 25.38]\n",
      " [25.81 25.63]\n",
      " [25.88 25.75]\n",
      " [25.88 25.94]\n",
      " [26.   26.  ]\n",
      " [26.06 27.06]\n",
      " [26.06 27.19]\n",
      " [25.94 27.  ]\n",
      " [25.88 27.  ]\n",
      " [25.88 26.94]\n",
      " [25.81 26.88]\n",
      " [25.75 26.81]\n",
      " [25.81 26.81]\n",
      " [25.94 26.81]\n",
      " [26.   26.75]\n",
      " [26.06 26.81]\n",
      " [26.13 26.81]\n",
      " [26.13 25.88]\n",
      " [26.13 25.81]\n",
      " [26.19 25.81]\n",
      " [26.19 25.88]\n",
      " [26.19 26.  ]\n",
      " [26.25 26.13]\n",
      " [26.25 26.25]\n",
      " [26.25 26.31]\n",
      " [26.25 26.38]\n",
      " [26.25 26.31]\n",
      " [26.19 26.25]\n",
      " [26.25 26.19]\n",
      " [26.25 26.13]\n",
      " [26.25 26.13]\n",
      " [26.13 26.  ]\n",
      " [26.   25.88]\n",
      " [25.94 25.81]\n",
      " [25.88 25.81]\n",
      " [25.81 25.75]\n",
      " [25.81 25.75]\n",
      " [25.69 25.69]\n",
      " [25.69 25.63]\n",
      " [25.63 25.63]\n",
      " [25.63 25.63]\n",
      " [25.56 25.56]\n",
      " [25.5  25.56]\n",
      " [25.5  25.5 ]\n",
      " [25.5  25.5 ]\n",
      " [25.5  25.5 ]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.38 25.44]\n",
      " [25.44 25.38]\n",
      " [25.44 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.38]\n",
      " [25.38 25.44]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.31 25.38]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.25 25.31]\n",
      " [25.25 25.31]\n",
      " [25.25 25.25]\n",
      " [25.19 25.25]\n",
      " [25.25 25.25]\n",
      " [25.25 25.25]\n",
      " [25.19 25.25]\n",
      " [25.19 25.25]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.13 25.19]\n",
      " [25.13 25.13]\n",
      " [25.06 25.13]\n",
      " [25.13 25.13]\n",
      " [25.06 25.13]\n",
      " [25.06 25.13]\n",
      " [25.06 25.13]\n",
      " [25.06 25.19]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.   25.  ]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.   25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.25 25.19]\n",
      " [25.19 25.25]\n",
      " [25.25 25.25]\n",
      " [25.25 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.38 25.38]\n",
      " [25.31 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.44 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.38]\n",
      " [25.44 25.44]\n",
      " [25.38 25.38]\n",
      " [25.44 25.38]\n",
      " [25.44 25.38]\n",
      " [25.38 25.44]\n",
      " [25.38 25.44]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.31 25.38]\n",
      " [25.31 25.38]\n",
      " [25.31 25.38]\n",
      " [25.31 25.38]\n",
      " [25.31 25.38]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.25 25.31]\n",
      " [25.25 25.25]\n",
      " [25.31 25.25]\n",
      " [25.25 25.25]\n",
      " [25.25 25.31]\n",
      " [25.25 25.25]\n",
      " [25.25 25.25]\n",
      " [25.19 25.25]\n",
      " [25.19 25.25]\n",
      " [25.19 25.25]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.13 25.19]\n",
      " [25.13 25.19]\n",
      " [25.06 25.13]\n",
      " [25.06 25.06]\n",
      " [25.   25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.56 26.  ]\n",
      " [25.63 26.31]\n",
      " [25.69 26.31]\n",
      " [25.75 26.13]\n",
      " [25.75 26.06]\n",
      " [25.81 26.06]\n",
      " [25.81 26.  ]\n",
      " [25.94 26.13]\n",
      " [25.94 26.13]\n",
      " [25.94 26.19]\n",
      " [26.   26.25]\n",
      " [25.88 26.06]\n",
      " [25.81 25.94]\n",
      " [25.75 25.81]\n",
      " [25.69 25.75]\n",
      " [25.69 25.69]\n",
      " [25.63 25.63]\n",
      " [25.56 25.56]\n",
      " [25.56 25.56]\n",
      " [25.56 25.5 ]\n",
      " [25.5  25.5 ]\n",
      " [25.5  25.5 ]\n",
      " [25.5  25.44]\n",
      " [25.5  25.44]\n",
      " [25.44 25.44]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.38 25.38]\n",
      " [25.31 25.31]\n",
      " [25.38 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.31 25.31]\n",
      " [25.25 25.25]\n",
      " [25.25 25.31]\n",
      " [25.25 25.31]\n",
      " [25.25 25.25]\n",
      " [25.25 25.25]\n",
      " [25.25 25.31]\n",
      " [25.19 25.25]\n",
      " [25.19 25.19]\n",
      " [25.19 25.25]\n",
      " [25.19 25.19]\n",
      " [25.19 25.25]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.19]\n",
      " [25.19 25.13]\n",
      " [25.19 25.13]\n",
      " [25.19 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.19 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.13]\n",
      " [25.13 25.06]\n",
      " [25.13 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.06 25.06]\n",
      " [25.13 25.06]\n",
      " [25.13 25.06]\n",
      " [25.13 25.06]\n",
      " [25.06 25.06]]\n",
      "[1 1 1 2 2 2 2 2 3 3 2 3 3 0 0 0 0 0 1 1 1 1 1 2 2 2 2 3 3 3 3 3 3 3 3 3 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 2\n",
      " 2 2 2 2 0 0 0 0 0 0 1 1 1 1 1 2 2 2 2 3 3 3 3 3 2 2 2 2 2 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 3 3 3 3 3 3 3 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0]\n"
     ]
    }
   ],
   "source": [
    "# Take two columns as data and column `Room_Occupancy_Count` as target class. \n",
    "X = np.array(dataset[['S1_Temp', 'S2_Temp']])\n",
    "y = np.array(dataset['Room_Occupancy_Count'])\n",
    "print(X)\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SVM\n",
    "\n",
    "Ref: lab7-demo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.9/site-packages/sklearn/svm/_base.py:1206: ConvergenceWarning: Liblinear failed to converge, increase the number of iterations.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1080x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def make_meshgrid(x, y, h=.02):\n",
    "    \"\"\"Create a mesh of points to plot in\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    x: data to base x-axis meshgrid on\n",
    "    y: data to base y-axis meshgrid on\n",
    "    h: stepsize for meshgrid, optional\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    xx, yy : ndarray\n",
    "    \"\"\"\n",
    "    x_min, x_max = x.min() - 1, x.max() + 1\n",
    "    y_min, y_max = y.min() - 1, y.max() + 1\n",
    "    xx, yy = np.meshgrid(np.arange(x_min, x_max, h),\n",
    "                         np.arange(y_min, y_max, h))\n",
    "    return xx, yy\n",
    "\n",
    "\n",
    "def plot_contours(ax, clf, xx, yy, **params):\n",
    "    \"\"\"Plot the decision boundaries for a classifier.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    ax: matplotlib axes object\n",
    "    clf: a classifier\n",
    "    xx: meshgrid ndarray\n",
    "    yy: meshgrid ndarray\n",
    "    params: dictionary of params to pass to contourf, optional\n",
    "    \"\"\"\n",
    "    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "    Z = Z.reshape(xx.shape)\n",
    "    out = ax.contourf(xx, yy, Z, **params)\n",
    "    return out\n",
    "\n",
    "\n",
    "# we create an instance of SVM and fit out data. We do not scale our\n",
    "# data since we want to plot the support vectors\n",
    "C = 1.0  # SVM regularization parameter\n",
    "models = (svm.SVC(kernel='linear', C=C),\n",
    "          svm.LinearSVC(C=C),\n",
    "          svm.SVC(kernel='rbf', gamma=0.7, C=100),\n",
    "          svm.SVC(kernel='poly', degree=3, C=C))\n",
    "models = (clf.fit(X, y) for clf in models)\n",
    "\n",
    "# title for the plots\n",
    "titles = ('SVC with linear kernel',\n",
    "          'LinearSVC (linear kernel)',\n",
    "          'SVC with RBF kernel',\n",
    "          'SVC with polynomial (degree 3) kernel')\n",
    "\n",
    "# Set-up 2x2 grid for plotting.\n",
    "plt.rcParams['figure.figsize'] = (15.0, 10.0)\n",
    "fig, sub = plt.subplots(2, 2)\n",
    "plt.subplots_adjust(wspace=0.4, hspace=0.4)\n",
    "\n",
    "X0, X1 = X[:, 0], X[:, 1]\n",
    "xx, yy = make_meshgrid(X0, X1)\n",
    "\n",
    "for clf, title, ax in zip(models, titles, sub.flatten()):\n",
    "    plot_contours(ax, clf, xx, yy,\n",
    "                  cmap=plt.cm.coolwarm, alpha=0.8)\n",
    "    ax.scatter(X0, X1, c=y, cmap=plt.cm.coolwarm, s=20, edgecolors='k')\n",
    "    ax.set_xlim(xx.min(), xx.max())\n",
    "    ax.set_ylim(yy.min(), yy.max())\n",
    "    ax.set_xlabel('Temperature 1')\n",
    "    ax.set_ylabel('Temperature 2')\n",
    "    ax.set_xticks(())\n",
    "    ax.set_yticks(())\n",
    "    ax.set_title(title)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Decision Tree\n",
    "\n",
    "[Ref: Understanding the decision tree structure](https://scikit-learn.org/stable/auto_examples/tree/plot_unveil_tree_structure.html#sphx-glr-auto-examples-tree-plot-unveil-tree-structure-py)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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CtgQN2fKPRL6ZMNa1yBayJWjIln8kM1tyhPv6F9lCtgRNOmeLl3/v9BayJdUl6zhvuFI1xwpCbyFbUlU695YgdaRUyZZi8oFvvvlGzjkdeeSRBV7n/fffl3NO7du3z71s5cqVGjhwoNq1a6eaNWuqZMmSqlKlijp27KgpU6ZENINzTnXq1Am5b9myZXLOqW3btiH3T548WZ06ddJBBx2kzMxM1apVS7169dLKlSsjmiGoJkyYIEk6//zz5ZzLs69q1ao64YQTtHPnTk2aNCns+8zIyJAklSxZMub5VqxYoW+++UZZWVnq1KlTvv1du3aVJI0fP5610gi543+vvvqqJOnyyy/Ply05du3apR49eujggw/Wgw8+mMzxJEnZ2dmSpFWrVsXl/hKRp35YC3uRO/7gl9+fpUqV0uGHHy4pPhlCB0lt5EewjR49Wn/88YfOP/981a1bN6Frperv91R9XH5G7vhHOMdFKleuHPM6qdol9uzZoxdeeEGSdMstt8R8fyga+YFwJbMjffXVV5Kkdu3a5dvXpEkTVa5cWZs3b9ZHH30U81r0luQjd/whVbtEUYL6WhaKRrb4Q7pmC1IX2eIPZEtixfv1LxSNbPEHsgWphmxJP+mYY/SW5CNb/CFVf979ki3pxhcnIjVp0kRNmjTR999/r9mzZ4e8zsiRIyVJl112We5l48aN06233qoVK1aoUaNGOvfcc1W/fn1NmjRJ7du3z30TeyLdfffdOuWUU/S///1PDRo00Nlnn60KFSpoyJAhat68uRYsWJDwGbw2b948SVLz5s1D7m/WrFme6xVl7ty5ev3111W8eHGdeuqpMc83d+5cSVLjxo2VmZlZ4HxLlizR5s2bWStNkDv+tnr1ak2ePFmS1K1btwKv99BDD2nevHl66qmnVKFChWSNl2vRokWSpEMOOSQu9xfvPPXLWtiL3PEHv/z+3L17t5YtWyYpPhlCB0lt5Eew5byh9ZRTTtH69ev11FNPqXfv3rr55ps1ZswY7dixI25rperv91R9XH5G7vhHznGRe+65R7t27cq9fOvWrRowYIAk6V//+lfM66Rql/jhhx+0evVq1atXT/Xr19fHH3+svn37qlevXnrwwQf1ww8/xHT/yI/8QLiS2ZG2bNkiSapUqVLI/TkndM6ZMyfmtegtyUfu+EOqdomi5gjqa1koGtniD+mYLUhtZIs/kC2JFe/Xv1A0ssUf0iFbxo4dqz59+qhXr14aMGCAZs2aFbf7hv+QLeknHXJsf/SW5CNb/CFVf97pSN7wxYlIknTppZdK+idE9rV161a9/fbbKlWqlDp37px7+QknnKC5c+dq8eLF+uCDDzRmzBh98cUXmjVrlsqXL68+ffrkvsiYCOPGjdP999+vww47TPPmzdOMGTP05ptv6ttvv9XgwYO1Zs0ade/ePez7Gz58uJxzEW0FnZmZTMuXL5ck1ahRI+T+nMtzfmnvb+TIkerevbsuvvhiHX/88WrWrJm2bt2q/9/evQdZXdf/A38tl5W74oimYqB4AUIhL3nJFMR0FPGuIVSSpERppmYZ04yOX80/qKFGzBtpKl5SFG9YFgkl4ySTlYmKipj3ABEtNF2B9+8PfmfdZXf57OXsOZ89+3jMnGE4n3PO6/PZ3fP8vPbzOa/9XHvttTFs2LB2X78+ffrUDjAUHqtW5yB38ps7c+bMiQ0bNsShhx4aQ4YMafQxy5YtiyuuuCLGjx9f73tUKjU1NXHNNddERMQJJ5xQlNdsa57mtRafkjvlz5287D9vu+22WL16dQwYMCAOOeSQNr+eHqTyyY/y50drLV26NCIi/v3vf8fQoUPj/PPPj+uuuy5mzpwZZ5xxRnzuc5+LZcuWFaVWpe7fK3W78k7u5CN3ZsyYEcOHD4/Zs2fHkCFD4uSTT47jjz8+Bg8eHEuWLIkZM2bEWWed1eY6ldpLFDJ4yJAhMWHChBg7dmzMmDEjrr/++pg+fXqMGDEipk+f3qYaNCQ/8pEfeVfKHmnAgAER0XivsHHjxnjttdeaXN5S+pbykDvlz51K7SXqqqRzWTSPbJEt7VWLzk22yJb2qpUXxT7/RfPIFtnSXrXquvrqq+Pqq6+O66+/Pn784x/HgQceGOPGjYt33323aDXIF9lS/mwppc6QY5vTt5SHbCl/tlTq+12PVB7dyr0CBZMmTYpLLrkk7rrrrpgxY0Z07dq1dtm8efNi3bp1MWHChOjbt2/t/SNHjmz0tfbff//4zne+Ez/5yU/isccei/Hjx7fLOv/f//1fRGwKxOHDh9dbNnXq1Jg/f3489NBD8Y9//CNGjRqV+Xq77777Fq/80ZjtttuuRY9vD4XJwN69eze6vE+fPvUet7m//OUvccstt9T+v2fPnjFz5syifJCmOetXWMf333+/zVOOlVqrUsmd/OZOYUq9qXVLKcWUKVOie/futcNApXbJJZfEiy++GEOGDIlp06YV5TXbmqd5rcWn5E75cycP+89//etfcdFFF0VExJVXXhlbbbVVm19TD1L55Ef586O11q5dGxER06dPj6FDh8a8efNi1KhR8fLLL8eFF14YCxcujHHjxsXSpUujZ8+ebapVqfv3St2uvJM7+cidnXfeOR5//PGYOHFiPProo7Uflo/YdBWRYp0YqdReopDBCxcujI0bN8Zll10WZ511VvTo0SPuu+++uOCCC+Kqq66KwYMHxznnnNOmWnxKfuQjP/KulD3S6NGj44477oibbropjjnmmHrL5syZEx999FFEON7Skcmd8udOpfYSdVXSuSyaR7bIlvaqRecmW2RLe9XKg/Y4/0XzyBbZ0l61IiJGjRoVBx54YBxxxBGxyy67xOrVq2PRokUxffr0eOSRR2L8+PHx+OOPR5cuufl7+BSJbCl/tpRSJedYY/Qt5SNbyp8tlfp+1yOVR24GkXbaaac44ogjYsGCBfHHP/4xjjrqqNpljV1qraCmpiYeffTRWLJkSaxatSo+/vjjiIh46aWX6v1bbKtXr46///3vMXDgwDjggAMafcxhhx0WDz30UDz55JPNCpdDDz00Dj300CKvaelUVVU1en9KaYvPmzVrVsyaNSs+/PDDeOmll+Lqq6+Ob33rW/HAAw/EvHnz2ryTL9Rvav2as46dvValkjv5zJ2nnnqq9kMmp59+eqOPmTVrVjzxxBPxi1/8InbZZZcSr2HETTfdFDNnzoxevXrFXXfd1eYPxGyutXma91rInYjy506595/vv/9+HH/88fHuu+/GaaedFmeffXZRXlcPUvnkR/nzo7U2bNgQERHdunWL3/3ud7HzzjtHxKaDEvPnz4899tgjVqxYEXfccUdMmTKlKDUrdf9eqduVV3InH7nzz3/+M4477riIiLj33ntj9OjRUVNTE4888khcdNFFMXr06Lj33nvbfGC9UnuJQgavX78+zjvvvLj00ktrl02dOjU+/vjjOP/88+OKK64wiFRE8iMf+ZF3peyRLr744rjnnnti7ty5ceGFF8Z3v/vd6NevXzz88MNx3nnnRbdu3WL9+vVFPRmkbyktuVP+3KnUXqKuSjqXRfPIFtnSXrXo3GSLbGmvWuXWXue/aB7ZIlvaq1ZExPe+9716/x80aFCceeaZceSRR8Y+++wTTzzxRMydO7fJz/fQccmW8mdLKVVyjm1O31JesqX82VKp73c9UnnkZhApYtMl1xYsWBBz5sypDZdVq1bFggULYvvtt68XOBERzz77bBx//PGxYsWKJl+zPSdiIyLeeOONLf7QRkS888477bIOedGnT59Yu3ZtrFu3rtHlhUve1Z1QbUyvXr1i5MiRMXv27KiqqorZs2fHz3/+8/jhD3/YpvUr1G1q/Vqyjp21ViWTO/lTuBrSiSeeGP369Wuw/LXXXovp06fHAQccEOeee26pVy/uv//+OOecc6J79+4xd+7c2H///Yv22sXK07zVoj65U17l3H/+73//i+OOOy6eeeaZGDt2bNx2221Fe209SOcgPzqmvn37xjvvvBNHH3107QdsC3r27BkTJ06MGTNmxKJFi9r8IdtK3b9X6nZ1BHKnvD755JM47bTT4s0334wlS5bEfvvtV7vsrLPOiq233jpOPfXUOO+88+KYY46Jbt1af5ivUnuJus9v7GoFU6ZMifPPPz9ef/31ePnll2PIkCFtqsen5AdZStkjjRo1Km6//fb4xje+ETNnzoyZM2fWLhs5cmQcdNBBcf3110f//v3bVCdC31JOcqe8KrWXaEwlnMui+WRLeXWmbKFzkS3lJVuKrz3Pf9F8sqW8OmO27LzzzvGNb3wjfvazn8Vvf/vbiv+QbWclWzqPzpJj+pZ8kC3lVanvdz1SeeRqEOmUU06Jb3/72zFv3rz48MMPo1evXnHnnXfG+vXrY8KECQ0+UHHaaafFihUr4uyzz45p06bFkCFDok+fPtGlS5e44YYbYurUqUWZXtu4cWOD+wp/sXHAgAFx7LHHbvH5n/vc55pVZ/HixTF79uwWrdt2220XP/3pT1v0nGIbNGhQrF27Nt54441GL4H3xhtv1D6uub7+9a/H7Nmz44EHHmjzyZtC3cJ6bG7dunXx/vvvR0TEZz/7WbU6GbmTr9z55JNP4s4774yIaPLyk4899lisW7cu3nvvvTjiiCPqLfv3v/8dERF/+MMfYvTo0dGnT594+OGHi7Z+CxYsiAkTJkRKKebMmRPHHHNM0V47on3yNA+1qE/ulDd3yrX/rKmpiZNOOikWL14cBx10UDzwwANFvbSzHqRzkB/56luaa/DgwfHKK680uU8dPHhwRESsXLmyzbUqdf9eqdvVEcid8ubOX/7yl3jxxRdj9913rzeEVHDiiSdGdXV1vPrqq7FixYrYc889W12rUnuJQsbWrVtX7969Y8CAAbF69epYuXKlQaQikh8ds28ppVL2SBGbfsYOP/zwuPvuu+O5556Lbt26xUEHHRSnnnpq7V9XHDFiRJvr6FvKR+50nuMteTou0VHPZdF8skW2tEctkC2ypT1qlUt7n/+i+WSLbGmPWlkKx6Tfeuutdq1D+ciWznOctzPkmL4lP2SLvqWj18rSmXqkXA0i9enTJ0488cS444474v7774+JEyc2eam1559/Pp5//vnYb7/94oYbbmjwWsuXL29R7e7duzc5Bffqq682uG+XXXaJiIitt946fv3rX7eoVlOWL18et9xyS4ueM2jQoLI3LqNGjYp//OMf8dRTT8W4ceMaLP/b3/4WEdHoidembLfddhGx6bJ2xVi/iIilS5dGTU1NVFdXN7p+u+66a6NXX1GrssmdfOXOb3/721i9enXstNNO8eUvf3mLj33ppZeavKTmqlWrYtWqVbH11lsXbd2eeOKJOPHEE6OmpiZuvPHGdplUbo88zUMt6pM75c2dcuw/N2zYEJMmTYpHH300Ro4cGY888kj07t27KK9doAfpHORHvvqW5tp3331j4cKF8e677za6fM2aNRGx6fvbVpW6f6/U7eoI5E55c6dwkLSpv8jUtWvX6N27d9TU1DSZMc1Vqb3EPvvsE127do0NGzbEu+++2+BqJxs3bqw94FyMHOZT8qNj9i2lVMoeqWD77bdvcHXt9evXx6JFiyIiYsyYMW2uoW8pH7nTeY635Om4REc9l0XzyRbZ0h61QLbIlvaoVQ6lOP9F88kW2dIetbKsXbs2IsJ7v4LJls5znLfSc0zfki+yRd/S0Wtl6Uw9Updyr8DmvvrVr0ZExJw5c+KFF16Iv/71rzF06NDYf//96z2u8E0qvMnrqqmpifvuu69FdXfaaadYs2ZNoycLHnnkkQb37bzzzjF8+PBYvnx5PPPMMy2q1ZTJkydHSqlFt8Jl38pp/PjxERFxzz33NJgqffvtt+Pxxx+Pbt26ZU6D1vWnP/0pIiJ23333Nq/foEGDYu+9946PPvooHnzwwQbLf/Ob30RExAknnKBWJyV38pM7hQbra1/7WnTp0vguakvrfPPNN0dExKRJkyKlFO+9915R1uvpp5+OcePGxQcffBA///nPY8qUKUV53c21R57moRYNyZ3y5U6p958ppTj77LNj7ty5sddee8Xvf//7Bh+ALQY9SOchP/LTtzRX4b2wePHiWL9+fYPlCxcujIhNH8Ztq0rdv1fqdnUUcqd8ubPjjjtGRMQLL7wQ//nPfxosX758ee3Xve6Vf1qjUnuJbbbZJg4//PCI+DRv61q8eHHU1NREr169YujQoW2uR33yo+P1LaVUyh5pS2677bZYtWpVHHbYYTFs2LA2v56+pbzkTuc43pKn4xId9VwWLSNbZEuxa0GEbJEtxa9VaqU6/0XLyBbZUuxaW5JSinvvvTciosHPGJVFtnSO47yVnGP6lnySLfqWjlxrSzpdj9TSH+a23jaVbNr69evTDjvskLp165bOOeecFBHpiiuuaPC4lStXpi5duqR+/fqlZcuW1d5fU1OTpk2bliIiRUS69NJL6z3vzDPPTBGRFi5cWO/+yZMnp4hI06ZNSxs3bqy9//7770/V1dUpItLhhx9e7zl33313iog0dOjQtGTJkgbruHr16jRr1qz04YcfbnGbS2XhwoUpItKZZ57Z7Od88YtfbPTrVdcnn3yS9txzzxQR6aqrrqq9/+OPP07jx49PEZHOOeeces959tln0w033JA++OCDBq83f/78tO2226aISPfcc0+D5YMGDcpcp83deuutKSLSrrvumt58883a+//0pz+l7t27p+rq6vTKK690mlqb18zy/x9T8rwoxq052yd32k9LcmfNmjW12/3cc8+1qt7NN9+cIiJNmjRpi8s3/7puyYsvvpi23377FBHpyiuvbPG6tKRWa/K01LU2r7n5z/vmOnJ+tPYmd8qrOblTyn31BRdcUFvrjTfeaPbz9CDyoynyo/201+9LKaV06KGHpohIF198cdqwYUPt/dddd12KiNSjR4/0+uuv13tO3nuJzf3hD39o1mvoW/J1kzvllZU7H330UfrMZz5T+ztO3fVes2ZNGj16dIqI9KUvfanBcyu1l2hNrUI+DRw4MD3//PO197/99ttp1KhRKSLSueee2+Tz9S3yI6WOlx+NaW7fUld77t9TKl2PlFJq9Ps6f/781KdPn1RdXZ2efvrpBsv1Lfm6yZ3yytvxllLV6ijnsjavuSWdMT+2dJMt5dVZs6Uxze3VSllr85pbIltki2xpWqVmS2vPf21ec0tki2yRLU0rVa1ly5al++67L33yySf17n///ffTN7/5zRQRqXfv3untt98uynZtTt8iW2RLQ+25f6/EHEtJ31KOm2wpr87at5SyVlt6pM1rbklHyJZcBsz3vve92nCoqqpq8qD61KlTU0SkrbbaKh177LHp9NNPTwMHDky9evVK5557bovCZdmyZal3794pItLw4cPTqaeeWvthhEsuuaTJE46XX355qqqqSlVVVWnUqFHplFNOSccdd1zaZ599Uvfu3VNEpLVr12Zucyk0J1yeeuqpdOCBB9be+vbtmyIiDRs2rPa+yy+/vMHz/vrXv6Y+ffqkiEj77bdf+spXvlL7JhkxYkR67733Gl2Xfv36pTFjxqSJEyemcePGpT322KP2e//973+/0XXcZZddUkSkxYsXN3vbN27cmCZOnFhb8+STT05HHXVU6tq1a6qqqko33nhjp6pVYBDpU3KnfbTkF6ZrrrkmRUQ64IADWl0vaxDpV7/6VYqIdOSRRzb7NQvfk/79+6czzzyzyVsxaqXU8jwtda0CH4yROx05d0q1r77//vtrv8djxoxpMj/mzZvX5lql3K621CqolF+min2TH+XVnr8vrVixIu24444pItIee+yRTjnllDRy5MgUEalbt27p9ttvb/CcjtBLTJs2rXa7hw0bliIi9e3bt97X6K233irbdhXoW+ROR86dhx9+uPag94477piOP/74dMwxx6T+/funiEgDBgyoN1xTUKm9RGtqpZRqf2Z69uyZxo4dm4499ti0zTbb1P4Oum7duiafq2+RHx01P1rbt5Ry/17KHiki0m677ZbGjRuXJkyYkPbee+/aXHjggQcafY6+JV83uVNeeTreUspaHeVcVoG+RbakJFsK8pwtKbW+VytlrQLZIltSki0FsmWTtpz/KpAtsiUl2VKQ52wpbPe2226bDj744HT66aensWPH1v5Rht69e6f58+cXbbv0LbKlLtmySSl/d6jEHNO3yBbZ0rhKfL+XslZbeqSCSsmWXAbMU089VRsujf1V14L169enX/ziF2nvvfdOPXv2TAMGDEgnn3xyWrp0aZMn7JoKl0Ldo48+OvXt2zf16tUrHXzwwenBBx9Mr7zySpPhklJKTzzxRDrjjDPSwIEDU/fu3VP//v3TiBEj0pQpU9L8+fPrTU2WU3PCpfCYLd2aev5LL72UJk2alHbYYYdUXV2ddtttt/SDH/wg/fe//23w2FWrVqXLL788jR07Ng0cODBttdVWqUePHmm33XZLkyZNSn/+858brfHOO++kqqqqtMcee6T169e3aPs3btyYfvnLX6bPf/7zqWfPnmnrrbdORx55ZFqwYEGnqlWXQaRPyZ320ZJBpC984QspItKsWbNaXS9rEOm8885LEZFuvfXWZr9m4X2SdStGrYKW5GmpaxX4YIzc6ei5U4p9deH7k3Xb/PunB9lEfjRNfrSP9v59aeXKlencc89NgwYNStXV1Wm77bZLJ510UnryyScbfXxH6CUOP/zwzK/H5gcL9S35usmd8mpu37J06dI0efLkNHjw4FRdXZ169OiRhg4dmi644IJG/4pSpfYSbamVUkpz585Nhx12WOrXr1/q0aNHGjFiRLryyisz/zqZvkV+dNT8aG3fUur9e6l6pAsvvDDtu+++aZtttknV1dVp8ODBaerUqWnFihVNPkffkq+b3CmvPB1vKWWtjnAuqy59i2wpkC35zpaUWterlbJWXbJFthTIFtlS0NrzX3XJFtlSIFvynS1vvvlmuuCCC9IhhxySdtxxx1RdXZ169eqVhg8fns4///wmj6voWzrOTbaUV3sd5817tpSylr5FtsiWplXa+72UtVrbI9VVKdmS24Ch+FoyEJBXhUvczZkzR60iMIhEe8tb7gwfPjzttdderfrQmlr1+WCM3Mmr9sqdSu0L8tyDyA9KTd9SebUK9C1yJ6/0LfmtVZe+RX7kkb6l8moV6FvkTl7pW/Jbqy59i2zpaGRLfmvVJVtkS0cjW/Jbqy7ZIls6GtmS31p1yRbZ0tHIlvzWqku2yJaORrbkt1ZdlZIt3YJOZ/HixTF58uSIiJg5c2b079+/vCvUAo899lgMGzYszjjjDLVa6cknn4xrr702IiLeeeeddq8HEfnInZUrV8Zzzz0Xd9xxR3Tt2lWtVvrRj34Ub7/9dixfvrzda0FbFDt3KrUv0INAQ/qWyqgVoW+h49C35K+WvoWOQt9SGbUi9C10HPqW/NXSt1AJZEv+askWKoFsyV8t2UIlkC35qyVbqASyJX+1ZAuVQLbkr1YlZkvVpoGpEhasqkqlrskmixYtijFjxtS77/XXX4+BAweWaY0oh7vuuqtBYGa9J6uqqiKlVNWe69VeZE55yZ3KM3To0HjhhRdq/3/ppZfGZZdd1uTjO3J+tJbcKS+5k18t7UHkB6UmPyqPviWb3CkvuZNf+pZs8qO85Efl0bdkkzvlJXfyS9/SNrKlvGRLfsmWtpEt5SVb8ku2tI1sKS/Zkl+ypW1kS3nJlvySLW0jW8pLtuRXJWaLQSQgU0cIs6bIHCivjpwfrSV3oDjkB1BqcgdoLfkBlJrcAVqrM+bHlsgWKA7ZUp9sgeKQLfXJFigO2VKfbIHikC31yRYojo6QLV3KvQIAAAAAAAAAAAAAAABA/hlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADJ1K3XBHj16rKyqqtqh1HWB1uvRo8fKcq9Da8kcKK+OnB+tJXegOOQHUGpyB2gt+QGUmtwBWqsz5seWyBYoDtlSn2yB4pAt9ckWKA7ZUp9sgeKQLfXJFiiOjpAtVSmlcq8DAAAAAAAAAAAAAAAAkHNdyr0CAAAAAAAAAAAAAAAAQP4ZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMhlEAgAAAAAAAAAAAAAAADIZRAIAAAAAAAAAAAAAAAAyGUQCAAAAAAAAAAAAAAAAMv0/tGHEWO9lEoAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 4320x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, random_state=7, test_size=0.3, stratify=y)\n",
    "clf = tree.DecisionTreeClassifier(random_state=7, max_depth=4)\n",
    "clf.fit(X_train, y_train)\n",
    "plt.rcParams['figure.figsize'] = (60.0, 20.0)\n",
    "# Set figure to a customized size to have better appearance. \n",
    "plt.rcParams.update({\"font.size\":15})\n",
    "tree.plot_tree(clf)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ROC Curve\n",
    "\n",
    "[Ref: ROC Curve with Visualization API](https://scikit-learn.org/stable/auto_examples/miscellaneous/plot_roc_curve_visualization_api.html#sphx-glr-auto-examples-miscellaneous-plot-roc-curve-visualization-api-py)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import RocCurveDisplay\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (10.0, 5.0)\n",
    "X = np.array(dataset[['S1_Temp', 'S2_Temp']])\n",
    "y = np.array(dataset['Room_Occupancy_Count'] > 0)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42, test_size=0.3, stratify=y)\n",
    "svc = SVC(random_state=42)\n",
    "svc.fit(X_train, y_train)\n",
    "\n",
    "svc_disp = RocCurveDisplay.from_estimator(svc, X_test, y_test)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cross Validation\n",
    "\n",
    "Ref: lab8-demo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f8040d746d0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X_train[:,0],X_train[:,1], c=y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fold 1, Accuracy: 0.658\n",
      "Fold 2, Accuracy: 0.947\n",
      "Fold 3, Accuracy: 0.789\n",
      "Fold 4, Accuracy: 1.000\n",
      "Fold 5, Accuracy: 0.868\n",
      "Fold 6, Accuracy: 0.921\n",
      "Fold 7, Accuracy: 1.000\n",
      "Fold 8, Accuracy: 1.000\n",
      "Fold 9, Accuracy: 0.892\n",
      "Fold 10, Accuracy: 0.865\n",
      "Mean: 0.894, +- 0.011\n"
     ]
    }
   ],
   "source": [
    "#k-fold cross validation\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "\n",
    "kfold = StratifiedKFold(n_splits=10).split(X,y)\n",
    "\n",
    "scores = []\n",
    "lr = LogisticRegression(C=1, random_state=1)\n",
    "\n",
    "for k, (train,test) in enumerate(kfold):\n",
    "    lr.fit(X[train], y[train])\n",
    "    score = lr.score(X[test],y[test])\n",
    "    scores.append(score)\n",
    "    print(\"Fold %d, Accuracy: %.3f\" % (k+1, score))\n",
    "    \n",
    "print(\"Mean: %.3f, +- %.3f\" % (np.mean(scores), np.var(scores)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parameter Optimization\n",
    "\n",
    "Ref: lab8-demo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GridSearchCV(cv=10, estimator=SVC(random_state=1),\n",
      "             param_grid=[{'C': [0.01, 0.1, 1, 10.0, 100.0],\n",
      "                          'kernel': ['linear']},\n",
      "                         {'C': [0.01, 0.1, 1, 10.0, 100.0],\n",
      "                          'gamma': [0.01, 0.1, 1, 10.0, 100.0],\n",
      "                          'kernel': ['rbf']}],\n",
      "             scoring='accuracy')\n",
      "0.8996443812233286\n",
      "{'C': 0.1, 'gamma': 1, 'kernel': 'rbf'}\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "sc = StandardScaler()\n",
    "sc.fit(X)\n",
    "x_std = sc.transform(X)\n",
    "\n",
    "param_range = [0.01, 0.1, 1, 10.0, 100.0]\n",
    "param_grid = [{'C': param_range, 'kernel': ['linear']},\n",
    "            {'C': param_range, 'kernel': ['rbf'], 'gamma':param_range}]\n",
    "\n",
    "gs = GridSearchCV(estimator=SVC(random_state=1),\n",
    "                 param_grid = param_grid,\n",
    "                 scoring = 'accuracy',\n",
    "                 cv=10)\n",
    "gs = gs.fit(X, y)\n",
    "print(gs)\n",
    "print(gs.best_score_)\n",
    "print(gs.best_params_)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3.9.7 ('base')",
   "language": "python",
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